JOURNAL ARTICLE

Reasoning within Fuzzy Description Logics

Umberto Straccia

Year: 2001 Journal:   Journal of Artificial Intelligence Research Vol: 14 Pages: 137-166   Publisher: AI Access Foundation

Abstract

Description Logics (DLs) are suitable, well-known, logics for managing structured knowledge. They allow reasoning about individuals and well defined concepts, i.e., set of individuals with common properties. The experience in using DLs in applications has shown that in many cases we would like to extend their capabilities. In particular, their use in the context of Multimedia Information Retrieval (MIR) leads to the convincement that such DLs should allow the treatment of the inherent imprecision in multimedia object content representation and retrieval. In this paper we will present a fuzzy extension of ALC, combining Zadeh's fuzzy logic with a classical DL. In particular, concepts becomes fuzzy and, thus, reasoning about imprecise concepts is supported. We will define its syntax, its semantics, describe its properties and present a constraint propagation calculus for reasoning in it.

Keywords:
Computer science Description logic Fuzzy logic Knowledge representation and reasoning Semantics (computer science) Extension (predicate logic) Context (archaeology) Fuzzy set Set (abstract data type) Syntax Representation (politics) Theoretical computer science Artificial intelligence Object (grammar) Programming language

Metrics

526
Cited By
6.15
FWCI (Field Weighted Citation Impact)
57
Refs
0.97
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Semantic Web and Ontologies
Physical Sciences →  Computer Science →  Artificial Intelligence
Data Management and Algorithms
Physical Sciences →  Computer Science →  Signal Processing
Logic, Reasoning, and Knowledge
Physical Sciences →  Computer Science →  Artificial Intelligence

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